import pandas as pd
# Load in the csv named "position_frequencies.csv" you made in exercise 24
# Save it as position_freq
____ = pd.____('data/____', ____)
# ____
# Use plot.bar() with position_freq
# Assign a color as Teal and set opacity to 0.5
# Don't forget to add a title as "Canuck Player Positions"
# ____ = ____.____.____(____ = ____,
# ____ = ____,
# ____ = ____)
## Data Looping Excercise 1
# Modify this program so that it prints the number of records in the file that has the fewest records.
import pandas
fewest = ____
for filename in glob.glob('data/*.csv'):
dataframe = pandas.____(filename)
fewest = min(____, dataframe.shape[0])
print('smallest file has', fewest, 'records')
## Data Looping Excercise 2
Write a program that reads in the regional data sets and plots the average GDP
per capita for each region over time in a single chart.
data_files_list = glob.___('')
mean_gdp = []
for file in data_file_list:
df = pd.read_csv()
mean_gdp.append()
mean_gdp_df = pd.DataFrame(data= , columns=)
import pandas as pd
import altair as alt
# Load in the csv named "canucks.csv" the same way you did earlier
# Save it as hockey_players
hockey_players = pd.____('data/____', ____)
# ____
# Use alt.Chart() to create a chart object
# Use the .mark_bar() to create a bar plot
# Use the .encode() to specify the column to plot
# Assign a color as Teal and set opacity to 0.5
# Don't forget to add a title as "Canuck Player Positions"
# position_bar = alt.Chart(
# ____, width=500, height=300).____(
# ____='____', ____=____).encode(
# x='____',
# y='____').properties(____='____')
#____
import pandas as pd
import altair as alt
# Load in the csv named "canucks.csv" the same way you did earlier
# Save it as hockey_players
hockey_players = pd.____('data/____', index_col=0)
# ____
# Use alt.Chart() to create a chart object
# Use the .mark_bar() to create a bar plot
# Use the .encode() to specify the column to plot
# Assign a color as Teal and set opacity to 0.5
# Don't forget to add a title as "Canuck Player Positions"
# position_bar = alt.Chart(
# ____, width=500, height=300).____(
# ____='____', ____=____).encode(
# x='____',
# y='____').properties(____='____')
#____